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The interval between stadia marks in most surveying instruments is 10 mrad and gives a stadia interval factor of 100. The distance between the instrument and a stadia rod can be determined simply by multiplying the measurement between the stadia hairs (known as the stadia interval) by 100. The instrument must be level for this method to work ...
This ratio is known as the stadia constant or stadia interval factor. Thus the formula for distance is D = kS. where D is distance from the telescope to the rod; k is the stadia constant; S is the difference between the rod readings at the two stadia marks; For example, a typical stadia mark pair are set so that the ratio is 100.
This is converted to distance from the instrument to the stadia rod by multiplying the stadia interval by the stadia interval factor. If the stadia rod is not at the same elevation as the instrument, the value must be corrected for the angle of elevation between the instrument and the rod. The formula most widely used for finding the distances is:
In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale.. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation.
The original paper by Gerchberg and Saxton considered image and diffraction pattern of a sample acquired in an electron microscope. It is often necessary to know only the phase distribution from one of the planes, since the phase distribution on the other plane can be obtained by performing a Fourier transform on the plane whose phase is known.
The prediction interval is conventionally written as: [, +]. For example, to calculate the 95% prediction interval for a normal distribution with a mean (μ) of 5 and a standard deviation (σ) of 1, then z is approximately 2. Therefore, the lower limit of the prediction interval is approximately 5 ‒ (2⋅1) = 3, and the upper limit is ...
A tolerance interval (TI) is a statistical interval within which, with some confidence level, a specified sampled proportion of a population falls. "More specifically, a 100×p%/100×(1−α) tolerance interval provides limits within which at least a certain proportion (p) of the population falls with a given level of confidence (1−α)."
Sample sizes may be evaluated by the quality of the resulting estimates, as follows. It is usually determined on the basis of the cost, time or convenience of data collection and the need for sufficient statistical power. For example, if a proportion is being estimated, one may wish to have the 95% confidence interval be